Mathematical models for the characterisation of the dynamics of biological systems

Biological systems are constantly exposed to changing environments and adapt to them. That is, biological systems are capable of gathering information about their environments and processing them. This ability to gather and process information does not require sophisticated organs like the brain of an animal. For instance, slime mould — a large brainless amoeba-like cell — can solve computationally difficult problems in a relatively short time. Or, recent experiments suggest that common bean plants can detect the existence of objects in their vicinities. These, and countless other examples, beg the question how basic biological systems such as a single cell are capable of processing information. The aim of this project is to regard the interaction between biological systems and their environments as a communication channel, and to model and predict the dynamical behaviours of biological systems using techniques of communication theory. A strong background in modern stochastic analysis, and stochastic filtering theory in particular, would be ideal to develop this line of research.

The successful candidate will receive comprehensive research training related to all aspects of the research and opportunities to participate in conferences, workshops and seminars to develop professional skills and research network.

Applicants should have a minimum of a first class honours degree in mathematics, the physical sciences or engineering. Preferably applicants will hold a MMath, MPhys or MSc degree, though exceptional BSc students will be considered.

English language requirements

IELTS minimum 6.5 or above (or equivalent) with 6.0 in each individual category.

Data Science and Dynamics